Trends that will drive data storage innovation in 2022
It’s no secret that we’re living in an unprecedented enterprise data boom: by 2025, the volume of data created is expected to reach nearly 180 zettabytes, according to IDC.
Last year, enterprise data in India was estimated to have grown at an average annual rate of 45.2%, faster than the global data annual growth rate of 42.2%. India’s annual growth rate is 3rd the fastest among the countries studied in the world, behind only the United States (50.5%) and Australia (46.9%).
Enterprises are increasingly relying on data storage innovation to leverage enterprise data. With data being generated at overwhelming volumes, enterprises seek to overcome mass capacity challenges in the multicloud environment by ensuring that data is accessible, bandwidth and security are enhanced, and disaggregated composable architectures support transparent data movement. As a result, this year and beyond, the following five major data innovation trends have been identified:
Distributed storage networks: The emergence of decentralized consensus protocols and distributed ledger technologies enables new ways to store data in decentralized storage networks. These storage networks will become the basis of the next generation World Wide Web known as Web 3.0. The capacity of decentralized storage networks (DeStor) continues to grow, with hundreds of petabytes integrated.
Wider adoption of object storage by enterprises: With the explosion of payload data, the object store is becoming the standard for mass capacity because it offers advantages over traditional file stores, including prescriptive metadata, scalability, and lack of structure. hierarchical data. Storage systems benefit from greater intelligence embedded in datasets, and object stores provide that intelligence. The highlight of object storage is the development of a new application in combination with block storage to provide scalability and performance in a symbiotic manner. Many legacy file applications are also migrating to an object storage infrastructure to take advantage of the economies of scale that object storage provides.
Developing cloud-native software and applications generates dynamically provisioned storage: The interoperability of the container deployment model promotes agility and flexibility for enterprises and, over time, facilitates the transition to multi-cloud. Moving from manual storage provisioning to orchestrated provisioning enables better utilization of storage hardware while managing quality of service through storage class abstractions. The container storage interface creates an extensible management plane for persistent volume consumption using a declarative method of controlling vendor-standard and unique storage features.
Transition to post-quantum cryptography. Large investments in quantum computing technologies will likely result in computers powerful enough to weaken the security of classical cryptography. According to current estimates, this will happen between 2026 and 2031. A new class of cryptographic algorithms, known as post-quantum cryptography (PQC), is being developed and standardized to mitigate the potential threat from quantum computers . We expect the new PQC standards to be ready by 2024.
Fabrics will continue to be an important technology enabling disaggregated infrastructure. Unifying the interface and simplifying the architecture translates into efficiency gains and economies of scale. An example of recent innovation is the emergence of NVMe (non-volatile memory express) hard drives (demonstrated at OCP in November). CXL will allow the creation of compute and memory structures.
These trends underscore the need for enterprises to deploy smarter and more flexible storage architectures with the least amount of human intervention, not only to maintain business resilience, but also to become the engine of business growth. business and breakthroughs in innovation. High-capacity 20TB drives are on the rise, along with innovative data storage systems, to ensure large amounts of data move efficiently between endpoints, the edge, and the cloud. Ultimately, the innovations pave the way for businesses to maintain user data sovereignty while getting the most out of corporate data.
The opinions expressed above are those of the author.
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